Structuring Machine Learning Projects
结构化机器学习项目
- 专项课程Deep Learning深度学习第 3 门 · 共 5 门
课程笔记
1 篇Module 01ML Strategy
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- 01Why ML Strategy
- 02Orthogonalization
- 03Join the DeepLearning.AI Forum to ask questions, get support, or share amazing ideas!
- 04Single Number Evaluation Metric
- 05Satisficing and Optimizing Metric
- 06Train/Dev/Test Distributions
- 07Size of the Dev and Test Sets
- 08When to Change Dev/Test Sets and Metrics?
- 09Why Human-level Performance?
- 10Avoidable Bias
- 11Understanding Human-level Performance
- 12Surpassing Human-level Performance
- 13Improving your Model Performance
- 14Lecture Notes W1
- 15Machine Learning Flight Simulator (Introduction to the Quizzes)
- 16Andrej Karpathy Interview
Module 02ML Strategy
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- 01Carrying Out Error Analysis
- 02Cleaning Up Incorrectly Labeled Data
- 03Build your First System Quickly, then Iterate
- 04Training and Testing on Different Distributions
- 05Bias and Variance with Mismatched Data Distributions
- 06Addressing Data Mismatch
- 07Transfer Learning
- 08Multi-task Learning
- 09What is End-to-end Deep Learning?
- 10Whether to use End-to-end Deep Learning
- 11Lecture Notes W2
- 12Ruslan Salakhutdinov Interview
- 13Acknowledgments